• Proceedings of the Korean Society for Information Management Conference
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• 2011.08a
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• pp.29-34
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• 2011

최근 인용 네트워크 분석을 통해서 단일 문헌의 인용 영향력을 측정하려는 시도가 다양하게 전개되고 있다. 널리 알려진 PageRank를 보완하려는 일부 시도와 함께 h-index를 단일 문헌의 인용 영향력 측정에 적용한 단일문헌 h-index도 제안되었다. 이 연구에서는 Web of Science에서 검색한 계량정보학 분야 문헌집합을 대상으로 여러 측정 방식의 특징을 비교해본 후, 새로운 인용지수 2종을 제안하였다. 제안한 인용지수는 PageRank처럼 전역 네트워크 분석 방식인 지수 1종과 h-index처럼 지역 네트워크 분석 방식인 지수 1종으로서 상황에 따라 선택하여 사용할 수 있다.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.4
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• pp.221-238
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• 2020

This study aims to investigate the scholarly communications and citation influences in library and information science field by conducting journal citation network analysis. For data collection, four major journals in library and information science field were chosen and 4,471 of research papers and 18,424 of citation records were collected from Korean Citation Index. The results show that Journal of the Korean Society for Library and Information Science was the most influential journal with highest citation in LIS fields, while Journal of the Korean Society for Library and Information Science Management influenced other research fields.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.119-143
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• 2011

This study identifies the characteristics of recent citation-based indicators for assessing a single paper in the context of their co-relationships. Five predefined indicators were examined with three variants of h-index which are convened in this study; the formers are PageRank, SCEAS Rank, CCI, f-value, and single paper h-index and the latters are $h_S$-index, h1-index, and $h_S$1-index. The correlation analysis and cluster analysis were performed to group the indicators by common characteristics, after which the indicators were calculated with the dataset from KSCI DB. The results show statistical evidence that distinguishes h-index type indicators from others. The characteristics of the indicators were verified with citation frequency factors using correlation analysis. Finally, the implications for applications and further studies are discussed.

• Annual Conference on Human and Language Technology
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• 2006.10e
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• pp.89-97
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• 2006

과학기술 문헌에 대한, 정확한 인용 정의의 제공을 위해서는 인용 관계를 구성하는 인력에 대한 동명이인 문제가 우선적으로 해소되어야 한다. 본 논문에서는 정확한 저자 중심의 인용 관계 및 네트워크를 구축하기 위해 URI(Universal Resource Identifier)를 이용하는 방법을 제안한다. 본 연구의 특징은, 지속적으로 추가되고 갱신되는 인용 정보를 일관성 있게 유지하고 정확한 문헌으로의 접근성을 보장하기 위해, 시맨틱웹 기술의 하나인 URI를 문헌과 저자에 적용하여 저자 중심 인용 관계 및 네트워크를 구축한다는 것이다. 실험에서는, 국내 학술대회 발표 논문들로부터 2,872개의 저자 중심 인용 관계 쌍을 추출하였고, 이를 바탕으로 구축한 저자 인용 네트워크에서는 135개의 인용 네트워크 그룹을 발견할 수 있었다. 본 연구의 결과는 향후 국가과학기술인력 종합정보시스템에서 제공하는 인력 DB 및 과학기술정보 포털서비스인 YesKiSTi와의 연계를 통하여 새로운 개념의 다양한 연구자 네트워크 서비스를 제공할 수 있을 것으로 기대된다.

• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.117-122
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• 2022

최근 국내외 ESG 연구가 활발해지고 있는 가운데, ESG 연구는 급격한 양적 성장을 하고 있음에도 학술지의 질적 수준을 평가할 수 있는 계량적인 논문은 부족한 상태이다. 본 연구는 한국학술지인용색인(KCI)에서 경영학 분야 내의 KCI 인용지수를 활용하여 상위 10개의 학회를 선정하고 이들 간의 ESG 논문 인용빈도와 네트워크 분석을 하였다. 상호 인용빈도를 활용하여 연결망을 작성하고 네트워크 분석 관점에서 ESG 주제에 관한 각 학술지 간 상호인용빈도를 통해 주어진 학술지의 영향력지수(Impact Factor)와 중심성 지수를 기초하여 연구하였다. 이러한 연구를 바탕으로 학술지들이 핵심 문헌을 식별하고 학문 내 지적 구조를 규명하여 경영학 분야의 ESG 연구 동향을 파악하고자 한다. 본 연구는 국내 발간된 경영학 학술지의 ESG에 대한 학술지의 영향력 인용지수를 비교해 보고 나아가 경영학 학술지의 자기 인용 비율을 확인하고 경영학뿐만 아니라 타 학문 분야에서 경영학 관련 학술지에 대한 인용이 이루어질 수 있도록 다학제적 교류와 추가 연구의 필요성을 제기하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.459-461
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• 2024

본 논문은 국내 정보보안 분야 학술 연구에서 참고문헌 인용행태를 파악하고자 해당 분야 대표 학술지의 인용문헌 현황 및 패턴을 분석하였다. 실험데이터는 "정보보호학회논문지"를 대상으로 수록된 모든 논문과 참고문헌 정보를 수집하고 개별 학술지 및 학술대회의 식별 과정을 통해 구축하였다. 이를 기반으로 참고문헌 현황, 인용나이 통계 분석 결과와 동시출현네트워크 (학술지 및 학술대회)의 생성을 통한 네트워크 중심성 및 시각화 지도를 제시하였다.

• Journal of KIISE:Software and Applications
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• v.34 no.2
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• pp.150-159
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• 2007

For the construction of accurate scientific citation information, author disambiguation should be primarily resolved. This study proposes a method that utilizes URI(Uniform Resource Identifier) to create precise author citation networks. The adoption of URIs for representing authors and papers in this study enables us to maintain the integrity of constantly changing citation information and to guarantee the accessibility to the right literature. In experiments, we extracted 2,872 author-centric citation relation pairs from recent major IT-related proceedings written in Korean. From those, 135 citation network groups were discovered. The findings of this study are expected to be applied to a variety of researcher network services and scientific information portal services.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.4
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• pp.311-331
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• 2023

This study attempted to explore the characteristics of knowledge communication and investigate important research topics and key authors by analyzing major academic papers in the field of LIS in Korea for five years from 2018 to 2022. The research method collected and analyzed papers published for five years in four key journals in the field of domestic Library and Information Science from the Korean Citation Index (KCI) database. The paper was selected to extract the author data of the paper and the data of the reference, and network visualization was performed by conducting literature co-citation analysis and author co-citation analysis using Netminer. As a result of the analysis, it was possible to derive a pair of co-citations between authors, and it was confirmed that it is important to include multiple authors in the intellectual structure analysis in the academic field through co-citation frequency analysis among researchers. The literature confirmed the correlation between the topics of the paper, and it was found that research related to Library and Information Science was centered on the topics of library, digital, user, service, and data.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.171-190
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• 2024

This paper conducts a comparative analysis of citation patterns between journals and conferences using bibliometric and social network analysis on references from the 'Journal of the Korea Institute of Information Security and Cryptology (JKIISC)'. The results indicate that conference references slightly exceed journal references, with around 80% being international publications, highlighting Korean researchers' high dependency on overseas publications. Analysis of citation age shows trends of increasing immediacy citation rate, lengthening citing half-life, and shortening peak time, with domestic publications having higher immediacy citation rate and international publications having slower citing half-life. Mapping SCOPUS journals and ICORE conferences revealed that journal citations mainly come from 'Computer science' (32.3%), 'Engineering' (23.5%), 'Mathematics' (16.7%), and 'Social Cciences' (12.8%), along with other research fields (25.6%), while conference citations are predominantly in 'Cybersecurity and Privacy' with recent increases in 'Computer Vision and Multimedia Computation' and 'Machine Learning'. Co-citation network analysis shows higher degree centrality for conference groups and international publications. The co-citation frequency between different types of literature was highest between journals and conferences (36.9%), compared to within journals (34.3%) or within conferences (28.8%). Lastly, network visualization maps are presented to explore the structural connections among co-cited publications and their research fields. The results of this study suggest that the field of information security research in Korea effectively balances the use of journal and conference literature, indicating that the field is developing through a complementary relationship between these sources.